[FIXED] scatter or bubble plotting by value duplication

Issue

I have a set of sequences of numbers that are kept in a 2D list. Each element in the list is a sublist of varying lengths, say numbers in the range 1-10. Like this:

Lst = [[1,3,4,4,4,5],[2,7,2,3],[6,5,4,2,4],[2,4,5,7,5,4,2],[4,9,4,1,4,5,4]…]

Is there a way to draw plot these datas in scatter or bubble plotting with value duplication by use matplotlib? Each element in the list occupies a position on the X-axis, and all the values in the element are distributed in the corresponding Y-axis position, and the more times the value is repeated, the larger the size or dark color of the drawn point.

I already know how to use matplotlib plot scatter plotting, but I don't know how to plot a 2D list item on one Y-axis one by one.

Thank you.

Solution

You can just plot each sublist in a for loop:

import matplotlib.pyplot as plt
from collections import Counter
import numpy as np
Lst = [[1,3,4,4,4,5],[2,7,2,3],[6,5,4,2,4],[2,4,5,7,5,4,2],[4,9,4,1,4,5,4]]
plt.figure()
for i, j in enumerate(Lst):
    occurences, sizes = list(zip(*list(Counter(j).items())))
    plt.scatter(i*np.ones(len(occurences))+1, occurences, s=np.array(sizes)*50)

Output:

Edit: Fulfilling request for points to also become darker. Using the answer from here: Darken or lighten a color in matplotlib

import matplotlib.pyplot as plt
from collections import Counter
import numpy as np

def lighten_color(color, amount=0.5):
    """
    Lightens the given color by multiplying (1-luminosity) by the given amount.
    Input can be matplotlib color string, hex string, or RGB tuple.

    Examples:
    >> lighten_color('g', 0.3)
    >> lighten_color('#F034A3', 0.6)
    >> lighten_color((.3,.55,.1), 0.5)
    """
    import matplotlib.colors as mc
    import colorsys
    try:
        c = mc.cnames[color]
    except:
        c = color
    c = colorsys.rgb_to_hls(*mc.to_rgb(c))
    return colorsys.hls_to_rgb(c[0], 1 - amount * (1 - c[1]), c[2])

Lst = [[1,3,4,4,4,5],[2,7,2,3],[6,5,4,2,4],[2,4,5,7,5,4,2],[4,9,4,1,4,5,4]]
occurences, sizes = list(zip(*[list(zip(*list(Counter(j).items()))) for j in Lst]))
maximum = max(max(i) for i in sizes)

plt.figure()
for i, (j, k) in enumerate(zip(occurences, sizes)):
    plt.scatter(i*np.ones(len(j))+1, j, s=np.array(k)*50, color=[lighten_color('b', 2*m/maximum) for m in k])

Output:

Answered By - Nin17